Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Ayobi, Nicolas"'
Autor:
Pérez, Alejandra, Rodríguez, Santiago, Ayobi, Nicolás, Aparicio, Nicolás, Dessevres, Eugénie, Arbeláez, Pablo
Phase recognition in surgical videos is crucial for enhancing computer-aided surgical systems as it enables automated understanding of sequential procedural stages. Existing methods often rely on fixed temporal windows for video analysis to identify
Externí odkaz:
http://arxiv.org/abs/2407.17361
Autor:
Ayobi, Nicolás, Rodríguez, Santiago, Pérez, Alejandra, Hernández, Isabela, Aparicio, Nicolás, Dessevres, Eugénie, Peña, Sebastián, Santander, Jessica, Caicedo, Juan Ignacio, Fernández, Nicolás, Arbeláez, Pablo
This paper presents the Holistic and Multi-Granular Surgical Scene Understanding of Prostatectomies (GraSP) dataset, a curated benchmark that models surgical scene understanding as a hierarchy of complementary tasks with varying levels of granularity
Externí odkaz:
http://arxiv.org/abs/2401.11174
Autor:
Psychogyios, Dimitrios, Colleoni, Emanuele, Van Amsterdam, Beatrice, Li, Chih-Yang, Huang, Shu-Yu, Li, Yuchong, Jia, Fucang, Zou, Baosheng, Wang, Guotai, Liu, Yang, Boels, Maxence, Huo, Jiayu, Sparks, Rachel, Dasgupta, Prokar, Granados, Alejandro, Ourselin, Sebastien, Xu, Mengya, Wang, An, Wu, Yanan, Bai, Long, Ren, Hongliang, Yamada, Atsushi, Harai, Yuriko, Ishikawa, Yuto, Hayashi, Kazuyuki, Simoens, Jente, DeBacker, Pieter, Cisternino, Francesco, Furnari, Gabriele, Mottrie, Alex, Ferraguti, Federica, Kondo, Satoshi, Kasai, Satoshi, Hirasawa, Kousuke, Kim, Soohee, Lee, Seung Hyun, Lee, Kyu Eun, Kong, Hyoun-Joong, Fu, Kui, Li, Chao, An, Shan, Krell, Stefanie, Bodenstedt, Sebastian, Ayobi, Nicolas, Perez, Alejandra, Rodriguez, Santiago, Puentes, Juanita, Arbelaez, Pablo, Mohareri, Omid, Stoyanov, Danail
Surgical tool segmentation and action recognition are fundamental building blocks in many computer-assisted intervention applications, ranging from surgical skills assessment to decision support systems. Nowadays, learning-based action recognition an
Externí odkaz:
http://arxiv.org/abs/2401.00496
Autor:
González, Cristina, Ayobi, Nicolás, Escallón, Felipe, Baldovino-Chiquillo, Laura, Wilches-Mogollón, Maria, Pasos, Donny, Ramírez, Nicole, Pinzón, Jose, Sarmiento, Olga, Quistberg, D Alex, Arbeláez, Pablo
Publikováno v:
2023 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)
This paper introduces a novel benchmark to study the impact and relationship of built environment elements on pedestrian collision prediction, intending to enhance environmental awareness in autonomous driving systems to prevent pedestrian injuries a
Externí odkaz:
http://arxiv.org/abs/2308.13183
Publikováno v:
2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI), 10230819
We propose Masked-Attention Transformers for Surgical Instrument Segmentation (MATIS), a two-stage, fully transformer-based method that leverages modern pixel-wise attention mechanisms for instrument segmentation. MATIS exploits the instance-level na
Externí odkaz:
http://arxiv.org/abs/2303.09514
Autor:
Valderrama, Natalia, Puentes, Paola Ruiz, Hernández, Isabela, Ayobi, Nicolás, Verlyk, Mathilde, Santander, Jessica, Caicedo, Juan, Fernández, Nicolás, Arbeláez, Pablo
Publikováno v:
Medical Image Computing and Computer Assisted Intervention 2022
Most benchmarks for studying surgical interventions focus on a specific challenge instead of leveraging the intrinsic complementarity among different tasks. In this work, we present a new experimental framework towards holistic surgical scene underst
Externí odkaz:
http://arxiv.org/abs/2212.04582
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